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df_day = pd.read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/web-data/data/cases_country.csv")
data = pd.read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/web-data/data/cases_time.csv")
df_geo = pd.read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/web-data/data/cases_country.csv")
data = data[['Country_Region', 'Last_Update', 'Confirmed', 'Deaths', 'Recovered', 'Active']]
data['Last_Update'] = pd.to_datetime(data['Last_Update']).dt.date
data.dtypes
df_day = df_day[['Country_Region', 'Last_Update', 'Confirmed', 'Deaths', 'Recovered', 'Active']]
df_day.dtypes
df_day['Last_Update'] = pd.to_datetime(df_day['Last_Update']).dt.date
df_day.head()
df = pd.concat([data, df_day])
df
df_geo = df_geo[['Country_Region', 'Lat', 'Long_']]
df_all = df.merge(df_geo, on='Country_Region', how='left')
df_all.head()
import plotly.express as px
df_data = df_all.groupby(['Last_Update', 'Country_Region'])['Confirmed', 'Deaths'].max().reset_index()
df_data["Last_Update"] = pd.to_datetime( df_data["Last_Update"]).dt.strftime('%m/%d/%Y')
fig = px.scatter_geo(df_data, locations="Country_Region", locationmode='country names',
color=np.power(df_data["Confirmed"],0.3)-2 , size= np.power(df_data["Confirmed"]+1,0.3)-1, hover_name="Country_Region",
hover_data=["Confirmed"],
range_color= [0, max(np.power(df_data["Confirmed"],0.3))],
projection="natural earth", animation_frame="Last_Update",
color_continuous_scale=px.colors.sequential.Plasma,
title='COVID-19: Progression of spread'
)
fig.update_coloraxes(colorscale="hot")
fig.update(layout_coloraxis_showscale=False)
fig.show()
import cufflinks as cf
from IPython.display import HTML
HTML(fig.to_html())